Jet trimming

By D. Krohn, Jesse Thaler, Lian-tao Wang. 2009

684 citations recorded by the source corpus.

Initial state radiation, multiple interactions, and event pileup can contaminate jets and degrade event reconstruction. Here we introduce a procedure, jet trimming, designed to mitigate these sources of contamination in jets initiated by light partons. This procedure is complimentary to existing methods developed for boosted heavy particles. We find that jet trimming can achieve significant improvements in event reconstruction, especially at high energy/luminosity hadron colliders like the LHC.

Subfields: Nuclear and High Energy Physics, Natural Language Processing

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Nuclear and High Energy Physics

1. Cms Collaboration
2. Atlas Collaboration
3. A. Larkoski
4. Jesse Thaler
5. I. Moult
6. Benjamin Nachman
7. G. Salam
8. G. Soyez

In Natural Language Processing

1. A. Larkoski
2. G. Salam
3. Benjamin Nachman
4. G. Soyez
5. Jesse Thaler
6. K. Tilburg
7. S. Marzani
8. Luke de Oliveira

Citations in the corpus

• Learning Particle Physics by Example: Location-Aware Generative Adversarial Networks for Physics Synthesis (2017, methodology): “To mitigate the contribution from the underlying event, jets are are trimmed [29] by re-clustering the constituents into R = 0 .”
• Jet substructure at the Large Hadron Collider: A review of recent advances in theory and machine learning (2017, background): “Among the early jet groomers that have seen wide use experimentally are filtering [42], trimming [332], and pruning [333].”
• Jet shapes and jet algorithms in SCET (2010, background): “Recently, several groups have explored strategies to probe jet substructure to distinguish jets produced by light partons in QCD from those produced by heavier particles [1, 2, 3, 4, 5, 6, 7, 8], and methods to “clean” jets of soft radiation to more easily identify their origin, such as “filtering” ”
• Maximizing boosted top identification by minimizing N-subjettiness (2011, methodology): “The experimental and theoretical progress in jet substructure has been summarized in a report following the BOOST2010 workshop [14], where the various tagging methods were roughly grouped as follows: algorithmic procedures to directly identify subjets within a fat jet [15–21]; jet shape techniques t”
• Towards an understanding of jet substructure (2013, methodology): “Trimming [37], in the variant that is most widely used today, takes all the particles in a jet of radius R and reclusters them into subjets with a jet definition with radius Rsub < R.”
• Playing tag with ANN: boosted top identification with pattern recognition (2015, methodology): “While many methods to reduce the effects of pile-up have been suggested [20, 21], their interaction with the ANN tagger needs to be explored.”
• The Lund jet plane (2018, methodology): “A further possibility is to supplement pileup mitigation with methods such as filtering [3], trimming [92] or recursive soft-drop [93], applied only to larger subjets, in order to reduce their contamination from pileup.”
• Small-radius jets to all orders in QCD (2014, background): “Here we will consider general purpose “grooming” approaches, filtering [14] and trimming [15], which, for their general ability to remove pileup, could have applications also beyond boosted-objected studies.”
• Les Houches 2017: Physics at TeV Colliders Standard Model Working Group Report (2017, methodology): “For grooming and prong finding, ATLAS using trimming [643] uses while CMS uses the modified Mass Drop Tagger (mMDT) [640, 644] and its generalization, SoftDrop [645].”
• Jet-images: computer vision inspired techniques for jet tagging (2014, methodology): “Noise Reduction: The effects of noise in the jet-image from pileup are reduced using trimming [13].”
• Power counting to better jet observables (2014, methodology): “Several methods for jet grooming and pile-up subtraction have been presented [47, 73, 81–88], and are used by the experiments [6, 16–18, 21], but we will not consider them here.”
• Boosted objects and jet substructure at the LHC. Report of BOOST2012, held at IFIC Valencia, 23rd–27th of July 2012 (2013, methodology): “1 We refer to three related techniques as jet grooming: filtering [1], trimming [2] and pruning [3].”